Pitch Channel Control of a REMUS AUV with Input Saturation and Coupling Disturbances

The motion of an underwater vehicle is prone to be affected by time-varying model parameters and the actuator limitation in control practice. Adaptive control is an effective method to deal with the general system dynamic uncertainties and disturbances. However, the effect of disturbances control on transient dynamics is not prominent. In this paper, we redesign the L1 adaptive control architecture (L1AC) with anti-windup (AW) compensator to guarantee robust and fast adaption of the underwater vehicle with input saturation and coupling disturbances. To reduce the fluctuation of vehicle states, the Riccati-based AW compensator is utilized to compensate the output signal from L1AC controller via taking proper modification. The proposed method is applied to the pitch channel of REMUS vehicle’s six Degrees Of Freedom (DOF) model with strong nonlinearities and compared with L1AC baseline controller. Simulations show the effectiveness of the proposed control strategy compared to the original L1AC. Besides, the fluctuation in roll channel coupled with pitch channel is suppressed according to the performances of control tests.

[1]  Thor I. Fossen,et al.  Guidance and control of ocean vehicles , 1994 .

[2]  Xin Zhang,et al.  Adaptive sliding-mode attitude control for autonomous underwater vehicles with input nonlinearities , 2016 .

[3]  Timothy Prestero,et al.  Verification of a six-degree of freedom simulation model for the REMUS autonomous underwater vehicle , 2001 .

[4]  Wei He,et al.  Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints , 2016, IEEE Transactions on Cybernetics.

[5]  Pouria Sarhadi,et al.  State of the art: hardware in the loop modeling and simulation with its applications in design, development and implementation of system and control software , 2015 .

[6]  Changyin Sun,et al.  Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Jianbin Qiu,et al.  Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method , 2017, IEEE Transactions on Cybernetics.

[8]  Bing Chen,et al.  Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints , 2013, IEEE Transactions on Cybernetics.

[9]  Irene M. Gregory,et al.  Predictor-Based Model Reference Adaptive Control , 2009 .

[10]  Alireza Khosravi,et al.  L1 adaptive pitch control of an autonomous underwater vehicle , 2014 .

[11]  Vincent Creuze,et al.  Stability analysis of a new extended L1 controller with experimental validation on an underwater vehicle , 2013, 52nd IEEE Conference on Decision and Control.

[12]  Naira Hovakimyan,et al.  ℒ1 adaptive controller for nonlinear reference systems , 2011, Proceedings of the 2011 American Control Conference.

[13]  Huanqing Wang,et al.  Adaptive neural data-based compensation control of non-linear systems with dynamic uncertainties and input saturation , 2015 .

[14]  T. Prestero,et al.  Development of a six-degree of freedom simulation model for the REMUS autonomous underwater vehicle , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[15]  Hamid Reza Karimi,et al.  Output-Feedback-Based $H_{\infty}$ Control for Vehicle Suspension Systems With Control Delay , 2014, IEEE Transactions on Industrial Electronics.

[16]  Rui Yang,et al.  Parametric identification and structure searching for underwater vehicle model using symbolic regression , 2017 .

[17]  Okyay Kaynak,et al.  Tracking Control of Robotic Manipulators With Uncertain Kinematics and Dynamics , 2016, IEEE Transactions on Industrial Electronics.

[18]  Naira Hovakimyan,et al.  L1 Adaptive Control Theory - Guaranteed Robustness with Fast Adaptation , 2010, Advances in design and control.

[19]  Sophie Tarbouriech,et al.  Design of Anti-Windup Compensators for a Class of Nonlinear Control Systems with Actuator Saturation , 2013 .

[20]  Shyi-Kae Yang Observer-based anti-windup compensator design for saturated control systems using an LMI approach , 2012, Comput. Math. Appl..

[21]  Naira Hovakimyan,et al.  Comparison of architectures and robustness of model reference adaptive controllers and L1  adaptive controllers , 2014 .

[22]  Nicholas D Valladarez An Adaptive Approach for Precise Underwater Vehicle Control in Combined Robot-Diver Operations , 2015 .

[23]  Ming Li,et al.  Modeling of a Complex-Shaped Underwater Vehicle for Robust Control Scheme , 2015, Journal of Intelligent & Robotic Systems.

[24]  Alireza Khosravi,et al.  Model reference adaptive PID control with anti-windup compensator for an autonomous underwater vehicle , 2016, Robotics Auton. Syst..

[25]  Tapabrata Ray,et al.  Model-based adaptive control system for autonomous underwater vehicles , 2016 .

[26]  Vincent Creuze,et al.  A novel application of multivariable ℒ1 adaptive control: From design to real-time implementation on an underwater vehicle , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[27]  Vincent Creuze,et al.  L1 Adaptive depth and pitch control of an underwater vehicle with real-time experiments , 2015 .

[28]  Kevin A. Wise,et al.  Robust and Adaptive Control: With Aerospace Applications , 2012 .

[29]  Changyin Sun,et al.  Fuzzy Tracking Control for a Class of Uncertain MIMO Nonlinear Systems With State Constraints , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[30]  Jianbin Qiu,et al.  Adaptive Fault-Tolerant Control for Nonlinear System With Unknown Control Directions Based on Fuzzy Approximation , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[31]  Alireza Khosravi,et al.  Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations. , 2016, ISA transactions.

[32]  Matthew C. Turner,et al.  Anti-windup synthesis using Riccati equations , 2007, Int. J. Control.

[33]  Noel E. Du Toit,et al.  Robust adaptive control of Underwater Vehicles for precision operations , 2015, OCEANS 2015 - MTS/IEEE Washington.